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Table 1.

The nonlinear equation system’s norms are shown, and the COC is bolded and enclosed in parenthesis.

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Table 1 Expand

Fig 1.

Dynamics of proposed method when a line and circle intersect, the number of iterations are ten and tolerance is 0.01.

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Fig 1 Expand

Fig 2.

Dynamics of proposed method when a circle and circle intersect, the number of iterations are ten and tolerance is 0.01.

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Fig 2 Expand

Fig 3.

Dynamics of proposed method when a parabola and circle intersect, the number of iterations are ten and tolerance is 0.01.

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Fig 3 Expand

Fig 4.

Dynamics of proposed method when a hyperbola and circle intersect, the number of iterations are ten and tolerance is 0.01.

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Fig 4 Expand

Fig 5.

Numerical solution of Blasius equation.

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Fig 6.

Derivative of numerical solution of Blasius equation.

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Fig 6 Expand

Table 2.

COC of proposed method (2) for the numerical solution of Blasius equation.

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Table 2 Expand

Fig 7.

Numerical solution of Falkner-Skan equation for β =4 /3.

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Fig 7 Expand

Fig 8.

Derivative of numerical solution of Falkner-Skan equation for β =4 /3.

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Fig 8 Expand

Table 3.

COC of proposed method (2) for the numerical approximation of Falkner-Skan equation (β =4 /3).

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Table 3 Expand

Fig 9.

Numerical solution of Lane-Emden equation for n = 2.

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Fig 9 Expand

Fig 10.

Derivative of numerical solution of Lane-Emden equation for n = 2.

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Fig 10 Expand

Fig 11.

Numerical solution of nano-particles in fluid.

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Fig 11 Expand

Fig 12.

Derivative of numerical solution of nano-particles in fluid.

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Fig 12 Expand

Fig 13.

Numerical solution of natural convection (Pr = 1).

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Fig 13 Expand

Fig 14.

Derivative of numerical solution of natural convection (Pr = 1).

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Fig 14 Expand

Fig 15.

Numerically computing solution of 2-D partial differential equation.

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Fig 16.

Absolute error in the computed solution of 2-D partial differential equation.

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Table 4.

Average simulation elapsed times for the comparison of Newton and our proposed method.

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Table 4 Expand